The Multidimensional Success of Pixar Films Visualized

Overview

This vignette is to recreate an analysis on Pixar ratings that can be found here.

Setup

library(pixarfilms)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
library(patchwork)

Ratings

Rotten Tomatoes

pixar_films %>%
  left_join(public_response) %>%
  left_join(academy) # %>% 
#> Joining with `by = join_by(film)`
#> Joining with `by = join_by(film)`
#> # A tibble: 88 × 15
#>    number film     release_date run_time film_rating plot  rotten_tomatoes_score
#>     <int> <chr>    <date>          <dbl> <chr>       <chr>                 <dbl>
#>  1      1 Toy Sto… 1995-11-22         81 G           "A c…                   100
#>  2      1 Toy Sto… 1995-11-22         81 G           "A c…                   100
#>  3      1 Toy Sto… 1995-11-22         81 G           "A c…                   100
#>  4      1 Toy Sto… 1995-11-22         81 G           "A c…                   100
#>  5      1 Toy Sto… 1995-11-22         81 G           "A c…                   100
#>  6      1 Toy Sto… 1995-11-22         81 G           "A c…                   100
#>  7      2 A Bug's… 1998-11-25         95 G           "A m…                    92
#>  8      2 A Bug's… 1998-11-25         95 G           "A m…                    92
#>  9      2 A Bug's… 1998-11-25         95 G           "A m…                    92
#> 10      3 Toy Sto… 1999-11-24         92 G           "Whe…                   100
#> # ℹ 78 more rows
#> # ℹ 8 more variables: rotten_tomatoes_counts <dbl>, metacritic_score <dbl>,
#> #   metacritic_counts <dbl>, cinema_score <chr>, imdb_score <dbl>,
#> #   imdb_counts <dbl>, award_type <chr>, status <chr>
  # mutate(year = year(release_date)
  #        # best = case_when(
  #          
  #        )) %>%
  # ggplot(aes(x = ))

IMDb

Metacritic

Session information

sessionInfo()
#> R version 4.6.0 (2026-04-24)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.4 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] patchwork_1.3.2  lubridate_1.9.5  ggplot2_4.0.3    dplyr_1.2.1     
#> [5] pixarfilms_0.2.1 rmarkdown_2.31  
#> 
#> loaded via a namespace (and not attached):
#>  [1] gtable_0.3.6       jsonlite_2.0.0     compiler_4.6.0     tidyselect_1.2.1  
#>  [5] jquerylib_0.1.4    scales_1.4.0       yaml_2.3.12        fastmap_1.2.0     
#>  [9] R6_2.6.1           generics_0.1.4     knitr_1.51         tibble_3.3.1      
#> [13] maketools_1.3.2    bslib_0.11.0       pillar_1.11.1      RColorBrewer_1.1-3
#> [17] rlang_1.2.0        utf8_1.2.6         cachem_1.1.0       xfun_0.58         
#> [21] sass_0.4.10        sys_3.4.3          S7_0.2.2           otel_0.2.0        
#> [25] timechange_0.4.0   cli_3.6.6          withr_3.0.2        magrittr_2.0.5    
#> [29] digest_0.6.39      grid_4.6.0         lifecycle_1.0.5    vctrs_0.7.3       
#> [33] evaluate_1.0.5     glue_1.8.1         farver_2.1.2       buildtools_1.0.0  
#> [37] tools_4.6.0        pkgconfig_2.0.3    htmltools_0.5.9